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Data Science AnalyticsTop 9 Best Product Analytics Software of 2026
Compare product analytics software tools and use cases, covering options like Mixpanel, Matomo, and Pendo for product teams and analysts.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Search agents gather the source set and the review record, including transcriptions of video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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Mixpanel is the best pick for product teams that need fast funnel, retention, and segmentation analysis because event autocapture turns common UI interactions into structured tracking without heavy manual wiring, while Matomo fits privacy-sensitive teams who want self-hosted control over their analytics data and configuration.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Mixpanel
Event autocapture that generates structured tracking for standard UI interactions without fully manual event wiring.
Best for: Fits when product teams need fast funnel, retention, and segmentation analysis with warehouse export.
Matomo
Editor pickSelf-hosted deployment keeps Matomo’s analytics database and configuration under the organization’s operational control.
Best for: Fits when privacy-sensitive teams need owned analytics infrastructure and configurable product reporting.
Pendo
Editor pickIn-app guidance that targets users from the same analytics events used for funnels, segments, and journey views.
Best for: Fits when product teams want in-app guidance driven by governed event analytics and stable identity stitching.
Comparison Table
Mixpanel
enterpriseEvent-based product analytics with real-time funnels, retention, and A/B reporting.
Event autocapture that generates structured tracking for standard UI interactions without fully manual event wiring.
Mixpanel instruments product events and turns them into funnel analysis, retention cohort views, and behavioral segmentation across web/mobile sessions. The tool supports event autocapture to reduce manual tracking work and pairs it with an event taxonomy governance workflow for consistent property naming.
Mixpanel also offers a data export API for moving event data to warehouses and downstream systems. Dashboarding and reporting focus on conversion and engagement metrics like activation rate and stickiness rather than only aggregate dashboards.
- +Funnel and cohort analysis work directly from instrumented events
- +Event autocapture reduces tracking coverage gaps for common user flows
- +Extensible event property handling supports consistent reporting across teams
- +Data export API enables warehouse and downstream pipeline reuse
- –Identity resolution stitching can require careful setup to avoid user fragmentation
- –Query performance can slow with complex segmentation and high event cardinality
- –SDK instrumentation plus taxonomy governance takes discipline across releases
- –Deep custom dashboards take more configuration than canned reporting views
Marketing and growth teams
Track campaign-to-product conversion funnels
Better conversion visibility
Analytics teams and leadership
Standardize recurring product reporting
More consistent reporting
Show 2 more scenarios
Product feature owners
Measure adoption and repeated usage
Clear adoption evidence
Use event activity and behavioral segments to evaluate feature reach and ongoing engagement.
Product managers and experimenters
Evaluate funnels and retention changes
Behavioral experiment validation
Compare event-based funnels, activation, and retention after UX or product updates.
Best for: Fits when product teams need fast funnel, retention, and segmentation analysis with warehouse export.
Matomo
SMBOpen-source web analytics with product analytics features and privacy-focused tracking.
Self-hosted deployment keeps Matomo’s analytics database and configuration under the organization’s operational control.
Matomo On-Premise can run inside an organization’s infrastructure, while Matomo Cloud provides managed hosting with the same core reporting model. The JavaScript tracker, server-side tracking endpoints, mobile SDKs, and HTTP Reporting API support multiple collection patterns. Role permissions, site-level administration, privacy settings, and configurable dashboards suit teams with formal governance requirements.
Matomo supports funnel analysis, user flow inspection, segmentation, goals, and custom dimensions for product behavior studies. Advanced modules add heatmaps, session recordings, form analytics, and cohort reporting. The main tradeoff is that complex product analytics programs require more instrumentation design and administration than event-first tools, making Matomo suitable for privacy-sensitive SaaS teams with dedicated analytics ownership.
- +Self-hosted deployment supports direct control over analytics data and infrastructure.
- +Matomo Tag Manager centralizes tags, triggers, and variables across tracked properties.
- +Data export API supports automated extraction into internal dashboards and data workflows.
- +Consent management and IP anonymization support privacy-focused measurement.
- –Advanced funnels, cohorts, heatmaps, and session recordings rely on separate feature modules.
- –Self-hosted installations require server maintenance, upgrades, backups, and security administration.
- –The interface feels denser than event-first analytics products during complex investigations.
- –Native feature-flag integrations are limited.
Privacy-regulated organizations
Self-hosted product usage measurement
Greater data control
SaaS product teams
Activation and conversion reporting
Clearer activation priorities
Show 1 more scenario
Digital agencies
Multi-site client analytics
Centralized client reporting
One Matomo instance separates sites, users, roles, and dashboards across client properties.
Best for: Fits when privacy-sensitive teams need owned analytics infrastructure and configurable product reporting.
Pendo
enterpriseProduct analytics combined with in-app guidance and user feedback collection.
In-app guidance that targets users from the same analytics events used for funnels, segments, and journey views.
Pendo is a product analytics and in-app experience analytics tool that combines behavioral instrumentation with application intelligence for guiding product decisions. Its core capabilities include event analytics with funnel and path exploration, segmentation built around user identity resolution, and in-app guidance that uses the same usage data.
Pendo also supports event property governance workflows, which helps teams standardize what gets tracked and how it maps to reporting. Admin controls and configuration work are centered on managing instrumentation, permissions for data access, and operational support for analytics adoption.
- +In-app guidance targeting tied directly to behavioral analytics.
- +Strong segmentation powered by anonymous-to-known user merge.
- +Event taxonomy governance helps keep reports consistent over time.
- +Flexible integrations through documented APIs and data export options.
- –Requires careful event property design to avoid reporting drift.
- –Identity resolution adds operational complexity for edge cases.
- –Some advanced analytics workflows depend on specific connectors.
- –Governance and RBAC setup can take time in larger orgs.
Product managers and growth teams
Measure feature adoption by behavior segments
Identify adoption gaps faster
Analytics administrators
Standardize events and identity context
More consistent analytics outcomes
Show 2 more scenarios
Customer success and onboarding teams
Guide activation with in-app checklists
Users reach activation milestones
Create in-product walkthroughs tied to the same usage data for targeting.
Product managers and research teams
Interpret in-product feedback with usage context
Better qualitative and behavioral alignment
Collect surveys inside the app and relate responses to behavioral and feature adoption signals.
Best for: Fits when product teams want in-app guidance driven by governed event analytics and stable identity stitching.
Amplitude
enterpriseProduct analytics platform for event tracking, funnel analysis, and user journey insights.
Amplitude’s event-to-segment workflow ties identity resolution and behavioral slices directly into funnel and retention analysis.
Amplitude pairs event-based product analytics with a strong experimentation and behavioral analysis workflow across web and mobile apps. It supports event instrumentation centered on consistent naming, identity resolution for user journeys, and rich segmentation for funnel and retention questions.
- +Behavioral segmentation with retention cohort and funnel views in one analysis flow
- +Experimentation reporting that tracks variant exposure and downstream conversion
- +Warehouse-native export paths for analysis handoff to data teams
- +Extensible ingestion and query APIs for custom dashboards and automation
- –Event taxonomy governance requires ongoing discipline to prevent reporting drift
- –Complex identity stitching can increase time-to-correctness for early setups
- –Large-scale queries can feel slower without careful instrumentation and filters
- –Advanced automations add operational overhead for admin and data governance
Digital analytics teams
Analyze web and mobile user journeys
Clear cross-platform journey visibility
Growth and marketing analysts
Measure campaigns through downstream product events
Behavior-based channel performance
Show 2 more scenarios
Product analytics teams
Track retention after release changes
Sharper release impact insight
Compare engagement for cohorts exposed to different releases or experiences.
Experimentation teams
Evaluate A/B tests with shared metrics
More consistent experiment outcomes
Use consistent event definitions, funnels, and cohorts to compare experiment effects.
Best for: Fits when product teams need governed event analytics plus experimentation and warehouse export for cross-team use.
LogRocket
SMBSession replay and product analytics for debugging user experience issues.
Replay recordings that correlate user actions with runtime console and network evidence during investigations.
LogRocket focuses on session replay plus application telemetry, with a viewer that ties user behavior to network and console signals. It captures client-side context through its JavaScript SDK and then lets teams analyze journeys with funnels, retention-like views, and event-based reporting.
- +Session replay includes errors, console output, and network context for faster debugging
- +Event reporting supports funnel analysis and behavioral views without leaving the replay workflow
- +Performance traces show client-side timing details alongside user actions
- +Data export options support moving captured events into external analytics stacks
- –Identity resolution stitching is limited compared with dedicated cross-platform identity graph tools
- –Complex event tracking still requires disciplined instrumentation and event property governance
- –Replay data volume can raise storage and ingestion overhead for high-traffic apps
- –Admin controls for multi-team environments are less granular than governance-first analytics systems
Product managers and analysts
Measure feature adoption through user funnels
Improved visibility into feature usage
Mobile and cross-platform developers
Diagnose errors with replayed sessions
Faster contextual issue diagnosis
Show 2 more scenarios
UX and engineering teams
Locate recurring stuck interaction points
Prioritized investigation targets
Aggregate interaction behaviors and replay evidence to identify where users repeatedly fail to complete actions.
Frontend engineers and product teams
Debug conversion-breaking checkout failures
Reduced conversion-blocking time
Inspect affected sessions with related error context to reproduce and resolve form submission and checkout issues.
Best for: Fits when teams need replay-grade debugging tied to event analytics in one workflow.
UXCam
SMBMobile product analytics with session replay and user journey tracking for apps.
Frustration signals automatically identify rage taps, dead taps, and u-turns inside replayable user sessions.
UXCam is strongest for mobile teams that need more than event counts. Session replay preserves the interaction context behind failed taps, abandoned flows, and repeated navigation, while screen analytics shows where users engage or stop. Frustration signals identify rage taps, dead taps, and u-turns so teams can prioritize interface defects with behavioral evidence.
- +Combines session replay with screen analytics and frustration signals
- +Rage taps, dead taps, and u-turns surface specific interaction failures
- +Funnels and retention cohorts connect behavior with product outcomes
- +Supports mobile SDK instrumentation, identity handling, and data exports
- –Consistent event and screen taxonomy requires developer coordination
- –Large apps can generate more replay volume than teams can review manually
- –Advanced analysis depends on adequate instrumentation and identity coverage
- –Desktop web analysis is less central than mobile app analysis
Mobile product teams
Investigating onboarding abandonment
Clearer onboarding defect priorities
UX research teams
Validating interface redesigns
Evidence-based design decisions
Show 2 more scenarios
Growth product managers
Diagnosing activation drop-offs
Faster activation diagnosis
Managers connect funnel losses with replay evidence to distinguish confusing interfaces from missing product value.
Mobile engineering teams
Investigating release regressions
Shorter regression investigations
Engineers correlate crash context and abnormal gestures with affected screens after application updates.
Best for: Fits when mobile product teams need replay evidence, screen analytics, and frustration diagnostics in one workspace.
June
SMBProduct analytics built for B2B SaaS with account-level reporting and lifecycle tracking.
Configurable dashboard templating paired with automation-ready metric queries to standardize KPI reporting across releases.
June is a product analytics and experimentation companion used to measure feature impact and user behavior over time. It combines event autocapture-style instrumentation with funnel and retention analysis views to turn raw events into repeatable performance reports.
- +Autocapture reduces manual event wiring for common product actions
- +Funnel and retention views support both acquisition and lifecycle analysis
- +Dashboard templates keep reporting consistent across teams
- +API and export options support deeper integration into analytics workflows
- –Advanced event property governance needs extra process discipline
- –Query performance depends on event volume and indexing choices
- –Cross-team attribution can require careful event naming and ID consistency
- –Some complex path and segmentation workflows may require more manual setup
Product managers and release teams
Compare feature journeys across releases
Behavioral impact visibility by release
Product managers and operations teams
Track feature usage adoption trends
Adoption signals for feature health
Show 2 more scenarios
Engineering and analytics teams
Validate event definitions and properties
More consistent reporting inputs
Review instrumentation consistency so dashboards and reports rely on stable event data.
Customer success and product ops
Assess engagement at account level
Account usage signals
Aggregate user activity into account-level metrics for customer health and engagement reviews.
Best for: Fits when teams want repeatable funnels and retention reporting with automated instrumentation and API-driven integration.
Indicative
enterpriseProduct analytics platform for funnel, cohort, and multi-channel journey analysis.
Journey Map visualizes event sequences and branching paths between selected product actions.
Indicative gives analysts a visual query builder for events, properties, users, accounts, and time windows. Journey Map reveals common and uncommon paths between product actions, while funnels, retention cohorts, and segmentation support activation and engagement analysis. Custom metrics and shared dashboards let teams standardize recurring reports without creating separate queries for each team.
- +Journey Map exposes multi-step paths that standard funnel reports can miss
- +Visual query builder supports funnels, cohorts, segmentation, and behavioral comparisons
- +Flexible event, user, account, and property data model
- +API and ingestion options support customer data pipeline integration
- –Identity stitching requires careful implementation across anonymous and known users
- –Advanced analyses depend on consistent event naming and property definitions
- –Session-level playback is not a core product capability
- –Dashboard governance needs deliberate ownership across larger teams
SaaS product teams
Analyze activation paths
Clearer activation priorities
Growth analytics teams
Compare conversion segments
More targeted experiments
Show 1 more scenario
Product operations teams
Monitor feature adoption
Consistent adoption reporting
Reusable dashboards track adoption, repeat usage, and retention across accounts, products, and release cohorts.
Best for: Fits when product teams need visual journey analysis across web, mobile, and account-level behavior.
Woopra
SMBCustomer journey analytics with end-to-end event tracking and real-time reporting.
Woopra provides real-time user journey context by merging identity and event streams into per-user timelines.
Woopra captures product events from web, mobile, and backend sources and turns them into user journeys, funnels, and retention views. The tool focuses on identity resolution so anonymous visitors can be stitched to known accounts for longitudinal analysis and lifecycle messaging.
- +Event-to-journey exploration connects funnels, paths, and user timelines
- +Identity stitching reduces anonymous fragmentation in retention analysis
- +Automation triggers tie behavioral conditions to downstream actions
- +API supports both event ingestion and data export for integrations
- –Event taxonomy governance needs disciplined property naming across teams
- –Advanced segmentation can require careful query building for accuracy
- –Some attribution questions depend on how events are modeled upstream
- –High event volume workloads can stress query performance without tuning
SaaS growth teams
Audit trial to paid journey behavior
Identify conversion barriers and friction
Lifecycle analytics teams
Analyze retention by behavior cohorts
Reveal churn drivers and signals
Show 2 more scenarios
Marketing and revenue teams
Track acquisition to conversion journeys
See full path to conversion
Connect events across campaigns, websites, and products through conversion milestones.
Conversion optimization analysts
Investigate funnel step drop-offs
Explain changes in conversion
Link funnel leakage to individual timelines and cohort characteristics for step-level diagnosis.
Best for: Fits when teams need user-level journeys with automation and an event API for integration control.
Conclusion
After evaluating 9 product analytics software, Mixpanel stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Product Analytics Software
Product analytics software ties tracked events to user journeys, funnels, and retention views so teams can diagnose feature performance and investigate failures with replay evidence. This guide covers UXCam, Indicative, Matomo, Amplitude, Mixpanel, Pendo, LogRocket, June, Woopra, and Smartlook with an emphasis on integration depth, automation surfaces, and governance controls.
The comparison favors tools with built-in instrumentation coverage like event autocapture or replay correlation, plus workflow options that connect event analysis to identity stitching and downstream sharing. Each tool’s strengths show up in mechanisms such as frustration signal detection in UXCam, journey branching in Indicative, and self-hosted control in Matomo.
Product Analytics Software for event-based funnels, retention, and replay-backed debugging
Product analytics software collects product interaction events from apps and web experiences, then turns them into behavioral analysis like funnels, cohorts, and path or journey views. Tools such as Mixpanel and Amplitude drive this from structured instrumented events, then extend analysis with segmentation and funnel plus retention workflows.
Beyond reporting, many products connect analytics outputs to operational debugging and guidance workflows. UXCam links replayable sessions to interaction failure signals like rage taps and dead taps, while Pendo ties in-app guidance targeting to the same governed event tracking used for funnels and segments.
Instrumentation coverage, workflow automation, and governance depth
Product analytics software turns tracked events into funnels, cohorts, and behavioral analysis, but execution quality depends on how consistently events and UI context stay connected. UXCam, LogRocket, and Smartlook each correlate replay playback to the same analytics events used for funnel and retention investigations.
Category value also depends on workflow automation and identity behavior, because teams rarely stop at reporting. Indicative and Amplitude add analysis workflows that visualize event sequences or tie event-to-segment decisions directly into retention and experimentation views.
Replay correlation with interaction failure signals
UXCam automatically flags rage taps, dead taps, and u-turns inside replayable user sessions and keeps those investigations tied to tracked behavior. LogRocket adds replay evidence with runtime console output and network context, while Smartlook keeps replay playback correlated to the same funnel and retention events.
Journey map and branching path exploration
Indicative builds a Journey Map that visualizes event sequences and branching paths between selected product actions across web, mobile, and account-level behavior. Woopra merges identity and event streams into per-user timelines so teams can trace funnels, paths, and user journeys in a single view.
Event autocapture for fast coverage of standard UI interactions
Mixpanel generates structured tracking from event autocapture so common UI interactions can feed funnel and cohort analysis quickly. June also uses autocapture to reduce manual wiring for common product actions while supporting automated metric queries for repeatable reporting.
Identity stitching and behavioral segmentation tied to analytics workflows
Amplitude connects identity resolution and behavioral slices directly into funnel and retention analysis through its event-to-segment workflow. Pendo uses anonymous-to-known user merge to drive segmentation and ties in-app guidance targeting to the same analytics events that power funnels and segments.
Owned infrastructure and centralized tag governance
Matomo supports self-hosted deployment so analytics data and configuration are controlled by the organization’s operations team. Matomo Tag Manager centralizes tags, triggers, and variables across tracked properties to reduce drift in instrumentation configuration.
Select by workflow fit, identity behavior, and operational control
The primary selection fork is whether debugging needs replay-first correlation or analytics-first journey modeling. UXCam and LogRocket focus on replay evidence linked to event analytics, while Indicative and Woopra emphasize journey exploration through branching maps or per-user timelines.
The second fork is whether the team wants quick coverage through event autocapture or governed event tracking that requires taxonomy discipline. Mixpanel and June reduce manual wiring using autocapture, while Amplitude and Pendo tie identity resolution and segmentation into broader analytics and guidance workflows that depend on consistent event property definitions.
Choose the primary investigation workflow: replay evidence or path visualization
Select UXCam or LogRocket when investigations must show what users did alongside runtime console and network evidence during failures. Select Indicative or Woopra when the main task is understanding branching paths or user-level journey timelines across funnels and behavioral views.
Decide between autocapture speed and governance discipline
Pick Mixpanel or June when fast instrumentation coverage is the priority because event autocapture generates structured tracking for standard UI interactions. Pick Amplitude or Pendo when event taxonomy governance and consistent property design are already part of the engineering operating model.
Match identity stitching expectations to the product identity reality
Choose Amplitude or Pendo when segmentation and retention views must use event-to-segment workflows that depend on identity resolution and anonymous-to-known merge. Choose Woopra when per-user timelines must merge identity and event streams into a single journey view with automated identity stitching.
Validate integration and automation surface for cross-team use
Use Amplitude when experimentation reporting needs variant exposure to connect directly into downstream conversion analysis and behavioral segmentation. Use June when standardized KPI reporting needs configurable dashboard templating and automation-ready metric queries across releases.
Constrain infrastructure and admin control where compliance requires it
Select Matomo when self-hosted control over analytics infrastructure and configuration is required for privacy-sensitive teams. Confirm Matomo feature module coverage for funnels, cohorts, heatmaps, and session recordings because advanced capabilities rely on additional modules.
Check how strongly replay or journey views depend on event naming consistency
If rage-tap and dead-tap diagnostics are a core workflow, confirm UXCam team coordination for consistent event and screen taxonomy. If path analysis needs correct branching and retention views, confirm Indicative and Woopra implementations use consistent event naming and property definitions.
Teams that get the most value from replay-linked analytics and governed tracking
Product engineering and product analytics teams benefit most when event behavior is traceable to what actually happened on the screen or in the client. UXCam fits teams that need replayable evidence plus interaction failure classification, while LogRocket fits teams that need console and network context during debugging.
Growth teams also benefit when analytics workflows connect to experimentation and in-app outcomes. Amplitude and Pendo tie behavioral analysis to experimentation exposure or in-app guidance targeting, which helps move from diagnosis to intervention within the same governed instrumentation footprint.
Mobile and cross-platform UX teams investigating interaction failures
UXCam produces frustration diagnostics like rage taps, dead taps, and u-turns inside replayable sessions so engineers can pinpoint specific interaction breakdowns.
Lifecycle and experimentation teams that require event-to-segment analysis in one flow
Amplitude combines retention cohort views with funnel analysis and experimentation reporting that tracks variant exposure into downstream conversion outcomes.
Product discovery teams mapping multi-step user journeys
Indicative’s Journey Map visualizes branching paths between selected product actions and its query builder supports funnels, cohorts, segmentation, and behavioral comparisons.
Privacy-sensitive orgs that need owned analytics infrastructure
Matomo’s self-hosted deployment keeps the analytics database and configuration under organizational operational control, and Matomo Tag Manager centralizes tags and variables.
Growth teams deploying in-app guidance tied to analytics events
Pendo ties in-app guidance targeting directly to the same governed event analytics used for funnels, segments, and journey views.
Common ways product analytics rollouts fail in practice
Many rollouts break when identity stitching assumptions do not match how identifiers behave in real traffic. Others fail when event properties are treated as ad hoc labels instead of a governed taxonomy used across funnels, cohorts, and replay correlations.
The result is either reporting drift where metrics stop lining up across teams or replay investigations that cannot be reliably correlated back to the event analytics workflow.
Allowing event and screen taxonomy to drift between teams that interpret replay output
UXCam’s frustration signals like rage taps and dead taps depend on consistent taxonomy, so create a shared event naming and screen mapping workflow before scaling replay volume.
Relying on identity stitching without defining how anonymous and known users should merge
Indicative and Amplitude both require careful identity stitching implementation, so confirm user merge behavior early by running retention cohort checks for fragmentation.
Building advanced funnel and cohort reporting on a minimal instrumentation footprint
Matomo’s advanced funnels, cohorts, heatmaps, and session recordings depend on separate feature modules, so validate module coverage before expecting full workflow parity with other tools.
Overloading segmentation queries without accounting for query latency during high event cardinality
Mixpanel notes slower query performance with complex segmentation and high event cardinality, so limit high-cardinality dimensions in early dashboards and iterate based on measured query behavior.
Treating autocapture as a replacement for property governance
June and Mixpanel can reduce manual event wiring using event autocapture, but advanced event property governance still needs extra process discipline to prevent reporting drift.
How We Selected and Ranked These Tools
We evaluated instrumentation workflows by scoring features that connect events to replay, journey maps, and behavioral segmentation, with a 40% weight on these capabilities. We scored ease and operational friction with a 30% weight using setup complexity signals and how quickly teams can use funnels, cohorts, and replay-linked investigations in practice.
We scored value with a 30% weight based on whether core workflows stay in one workspace instead of forcing manual cross-tool steps. UXCam ranked highest because replay evidence includes automatic frustration signals that identify rage taps, dead taps, and u-turns inside replayable sessions, which reduces time spent translating raw interaction logs into actionable failure patterns.
Frequently Asked Questions About Product Analytics Software
How do UXCam and Smartlook differ when validating mobile UI problems with session replay?
Which tool best supports journey sequencing beyond standard conversion reports?
What breaks when event taxonomy governance is inconsistent in Mixpanel or Pendo?
When should a team choose a self-hosted approach like Matomo over a hosted analytics stack?
How do Amplitude and Woopra approach identity resolution for longitudinal user journeys?
How do data export and API workflows differ between Mixpanel and LogRocket?
Which tool handles automated instrumentation with less manual event wiring using event autocapture?
When does dashboard templating matter for repeatable reporting across releases, and who covers it?
How do admin controls and access governance differ between Pendo and Woopra?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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